CN112587099B - Personalized Vital Signs Monitor - Google Patents

Abstract

Translated fromChinese

系统、方法和设备涉及使用患者特定范围监测生物状况(如生命体征)。示例性方法包括在第一时间段内从传感器接收自动确定的个人生命体征的第一测量值，并基于第一测量值，通过对第一测量值取平均值来确定生命体征基线。生命体征的阈值可以是基线的预定百分比。可以从传感器接收到生命体征的第二测量值。响应于确定第二测量值中的至少一个在该范围以外，警报可以被触发。

Systems, methods, and devices are directed to monitoring biological conditions (e.g., vital signs) using patient-specific ranges. An exemplary method includes receiving a first measurement of an individual's vital sign automatically determined from a sensor over a first time period, and determining a baseline for the vital sign based on the first measurement by averaging the first measurement. The threshold for the vital sign can be a predetermined percentage of the baseline. A second measurement of the vital sign can be received from the sensor. In response to determining that at least one of the second measurements is outside the range, an alarm can be triggered.

Description

Personalized vital sign monitor

Cross Reference to Related Applications

The present application claims priority from U.S. provisional application No.62/900,179 filed on day 13, 9, 2019, which is incorporated herein by reference in its entirety.

Technical Field

The present disclosure relates to vital sign monitors, and more particularly to vital sign monitors configured to provide an alarm or other indication when a patient vital sign falls outside of a personalized range.

Background

In a hospitalized clinical setting outside of an Intensive Care Unit (ICU), a single caregiver may be responsible for monitoring multiple patients. In some cases, the caregiver may actively measure the patient's vital signs and compare the vital signs to a predetermined range consistent with a healthy person. When the patient's vital signs are outside the patient's personalized range, the caregiver may initiate additional medical treatment for the patient. For example, vital signs may indicate that a patient requires intensive care and a caregiver may transfer the patient to the ICU. In an intensive care unit, the patient may be continuously monitored by a dedicated care unit.

However, as the number of patients for which the caregivers are responsible increases, the caregivers may measure vital signs less frequently. In non-emergency situations, in some cases, the caregiver may measure the patient's vital signs every 8 hours. While measuring the patient's vital signs at this frequency may allow the caregiver to monitor other patients as well, the patient's condition may deteriorate rapidly during the 8 hour sampling period. Thus, the caregivers are less likely to find early signs of patient deterioration and may not be able to initiate early intervention for the deteriorated patient.

An automatic sensor configured to automatically determine patient vital signs (without user intervention) may assist a caregiver in handling a large number of patient cases. Unlike manual measurement of vital signs, automatic sensors can measure vital signs of a patient without the presence or intervention of a caregiver. However, the fidelity of the vital sign measurement by the automatic sensor may be significantly lower than the quality of the vital sign measurement made directly by the caregiver. For example, in the case of measuring heart rate measurements, the automatic sensor may measure the heart rate of the patient, regardless of the patient's body position or the position of the sensor. In contrast, the caregiver will ensure that the patient is in a relaxed body position and the position of the sensor is ideal before measuring the patient's heart rate. Thus, some measurements measured by automatic sensors are more likely to be inaccurate than measurements measured directly by caregivers.

In some cases, the automatic sensor may measure vital signs semi-continuously, for example once per minute. However, many of these measurements may be inaccurate. When the caregiver is informed of each measurement that deviates from a particular threshold, noise in the measurement may increase the risk that the caregiver will be called to the patient's bedside when the patient is not experiencing distress. Noise may also increase the risk that the caregivers cannot be notified when the patient is in trouble. These risks are further exacerbated by natural vital sign changes between healthy patients and the relatively low fidelity measurement capabilities of automated sensors.

Disclosure of Invention

Various implementations of the present disclosure relate to vital sign monitors that trigger in response to vital signs being outside of a patient-specific range. A baseline vital sign may be identified for the individual, and a personalized range associated with the baseline vital sign may be further identified. A system that continuously (or semi-continuously) monitors individual vital signs may alert a caregiver when an individual vital sign is outside of a personalized range. Thus, if an individual's baseline is abnormal (e.g., greater or less than a global average), the vital sign monitor may not trigger a false alarm when the individual's vital sign is relatively close to the individual's baseline, even if the vital sign is outside of a health range defined for the global population. Furthermore, when an individual's vital sign is relatively far from the baseline of the individual, the vital sign monitor may trigger an alarm even if the vital sign is within a defined health range for the overall population. Thus, both the sensitivity and the specificity of the vital sign monitor can be enhanced according to different implementations.

Baseline vital signs can be identified in a number of different ways. In some cases, the baseline vital sign is determined by averaging the individual's various vital sign measurements over a period of time in which the individual's vital sign is relatively stable. In some cases, the baseline vital sign is the median of the vital sign measurements. In some cases, a vital sign is considered stable when the variance of the vital sign measurement is less than a threshold variance over the period of time. The threshold variance may be, for example, a fixed amount or percentage of the average vital sign of the individual over the period of time. As used herein, the term "average" may refer to an arithmetic average. In some cases, the baseline vital sign is determined from previous measurements of the vital sign during previous hospitalizations, admission procedures, primary care visits, and the like. According to various implementations, the baseline vital sign may be determined based on one or more measurements of the individual vital sign when the individual is medically stable.

In some cases, a baseline vital sign may be selectively identified when other features indicate that the vital sign of the individual is stable. For example, baseline vital signs may be determined from measurements taken while the individual is in a fixed position (e.g., supine position). In some cases, the baseline vital sign may be determined from measurements made when the individual moves less than a threshold amount. The position and/or movement of the individual may be identified using at least one of an accelerometer attached to the individual's body, a gyroscope attached to the individual's body, a pressure sensor on the individual's bed, and the like. In various implementations, an individual may be given a drug or other treatment that destabilizes their vital sign measurement. In some examples, the baseline may be determined from measurements that exceed a certain amount of time (e.g., one or more hours, depending on the pharmacokinetics of the drug, the dose and dosage form, and/or the measured bioavailability of the drug) after administration or other treatment.

The personalization range may be defined in terms of upper and lower thresholds. In some cases, at least one of the upper threshold or the lower threshold may be determined from a baseline vital sign. For example, the lower threshold may be a fixed amount less than the baseline vital sign, a predetermined percentage of the baseline vital sign (e.g., less than 100%), a predetermined percentage between the baseline vital sign and a minimum value of the vital sign (e.g., 50%), or a combination of both. In some examples, the upper threshold may be a fixed amount greater than the baseline vital sign, a predetermined percentage of the baseline vital sign (e.g., greater than 100%), a predetermined percentage between the baseline vital sign and a maximum value of the baseline vital sign (e.g., 50%), or a combination of both. In various implementations, both the lower threshold and the upper threshold may be identified based on baseline vital signs. In some cases, one of the lower and upper thresholds is determined from an overall value rather than a baseline of the individual. For example, the lower threshold and/or the upper threshold may be the same for all individuals in the overall population.

In various implementations, the sensor may measure vital signs of an individual. The monitoring system may compare the measured vital signs to the personalized range of the individual. If the system determines that the individual's vital signs are outside of the personalized range, the system may trigger an alarm. In some cases, the system may trigger an alarm if the vital sign of the individual is within a predetermined amount of time or a predetermined number of measured values are outside of a personalized range, which may prevent false alarms.

In various examples, the system can also monitor the rate of change of vital sign measurements and trigger an alarm based on the rate of change. In some cases, the rate of change may be an average rate of change based on a plurality of vital sign measurements. In some implementations, the system may compare the rate of change to a range and trigger an alarm when the rate of change is outside of the range. In various examples, the system may selectively trigger an alarm when the system identifies that the measured vital sign of the individual may be outside of the vital sign range and the rate of change is outside of the rate of change range. The range may be preset by the caregiver, automatically set based on historical trends of the monitored individual, automatically set based on previous analysis (e.g., based on previous studies indicating rates of change that may be associated with dangerous conditions such as heart attacks), etc. In some cases, the system may selectively trigger an alarm when the measured vital sign may be below the vital sign range and the rate of change may be below a first threshold, or when the measured vital sign may be above the vital sign range and the rate of change may be above a second threshold. Thus, the system can trigger an alarm based on the trend of the measured vital signs over time.

When the alarm is triggered, the electronic device may output a warning and/or alarm to at least one caregiver (e.g., nurse, doctor, etc.). In some cases, the alert and/or alarm may indicate the location and/or identity of the individual.

According to implementations of the present disclosure, various vital signs may be monitored. For example, at least one of heart rate, blood pressure, blood oxygen saturation percentage, respiratory rate, body core temperature, or peripheral temperature may be monitored.

Drawings

The following drawings forming a part of the present disclosure are illustrative of the technology and are not meant to limit the scope of the claims in any way.

Fig. 1 illustrates an example environment for continuously monitoring vital signs of a plurality of patients.

Fig. 2 shows an example of a visual interface output by a clinical device.

Fig. 3A and 3B illustrate examples of vital sign measurements performed semi-continuously over a period of time.

Fig. 4A and 4B show examples of individual vital sign measurements and rates of change.

FIG. 5 illustrates an example process for identifying personalized ranges of biological condition measurements that may be used to monitor an individual.

FIG. 6 illustrates an example process for triggering an alarm based on a measurement of a biological condition.

FIG. 7 illustrates an example system including at least one device. In some implementations, the system shown in fig. 7 may perform any of the functions described herein.

Detailed description of the preferred embodiments

Various implementations of the present disclosure will be described in detail with reference to the drawings, wherein like reference numerals represent like parts and assemblies throughout the several views. Moreover, any examples set forth in this specification are not intended to be limiting and merely set forth many possible implementations.

Fig. 1 illustrates an example environment 100 for continuously monitoring vital signs of a plurality of patients. In some cases, the example environment 100 may be associated with a medical facility. As at least shown with respect to fig. 1, the first through nth individuals 102-1 through 102-n may be monitored by the first through nth sensor devices 104-1 through 104-n, where n is a positive integer. As used herein, the terms "individual," "patient," and equivalents thereof may refer to a person who may be being actively monitored by a medical facility. In some implementations, the individuals 102-1 through 102-n may refer to individuals who are at least temporarily hospitalized in a medical facility. For example, the first individual 102-1 may be an individual that is monitored after a surgical procedure. In some implementations, the individuals 102-1 through 102-n may be monitored inside the ICU, outside the ICU, or in other environments where continuous care and supervision is provided by the medical provider. For example, individuals 102-1 through 102-n may be monitored in one or more medical wards.

The sensor devices 104-1 through 104-n may include sensors that measure, sense, detect, and/or otherwise determine various conditions of the individuals 102-1 through 102-n. As used herein, the terms "sensor," "biosensor," "vital signs sensor," and equivalents thereof may refer to a device configured to measure, sense, detect, and/or otherwise determine a biological condition of an individual. As used herein, the terms "biological condition," "condition," and equivalents thereof may refer to a physical parameter of an individual's body or a metric based on physical measurements of the individual's body. In some examples, the biological condition may be a vital sign (e.g., blood pressure, heart rate, body temperature, respiratory rate, blood oxygen saturation, etc.).

In some cases, the sensor may further report the measured biological condition to one or more external devices. Some examples of sensors include pressure sensors (e.g., pressure sensors mounted on a patient bed to sense the position of an individual lying on a patient bed), blood pressure sensors (e.g., blood pressure sensors including blood pressure cuffs, sensors that measure blood pressure based on pulse wave velocity, etc.), heart rate sensors (e.g., smart watch sensors), body temperature sensors (e.g., infrared thermometers), respiratory rate sensors (e.g., respiratory rate monitors), end-of-breath carbon dioxide sensors, blood oxygen saturation sensors (e.g., pulse oximetry and/or other sensors that measure peripheral blood oxygen saturation (SpO 2) in arterial blood), chemical sensors (e.g., glucose sensors), electrical sensors (e.g., electrocardiogram (ECG) sensors, electroencephalogram (EEG) sensors, etc.), consciousness sensors (e.g., devices that cause an individual to perform interactive psychological exercises), and so forth. Some of the sensors of the sensor devices 104-1 through 104-n may include movement sensors (e.g., gyroscopes, accelerometers, etc.), position sensors (e.g., pressure sensors on the beds of the individuals 102-1 through 102-n), and so forth.

According to some implementations, the sensor devices 104-1 through 104-n may measure patient condition multiple times within a time interval. In some cases, the sensor devices 104-1 through 104-n may sample the condition semi-continuously or periodically. As used herein, the term "semi-continuous" may refer to measurements performed at a sampling rate that meets or exceeds a minimum sampling rate defined according to the nyquist theorem (Nyquisttheorem). In some examples, any of the sensor devices 104-1 to 104-n may have a sampling rate of about 1-100 samples per minute, about 1-100 samples per hour, about 1-100 samples per day, and so forth.

The sensor devices 104-1 through 104-n may send data indicative of the measured values to the monitoring system 108 via the first network 106. In some cases, the sensor devices 104-1 through 104-n may measure various parameters (e.g., pressure, temperature, pulse frequency, electrical signals, etc.) associated with the individuals 102-1 through 102-n, generate signals indicative of the measured values based on the parameters, and send the signals to the monitoring system 108. In some cases, measurements may be derived by the sensor devices 104-1 through 104-n and/or the monitoring system 108 based on parameters. As used herein, the term "network" and its equivalents may refer to any suitable communication network through which a plurality of nodes may exchange data. Examples of networks include Wide Area Networks (WANs), such as the internet, individual area networks (PANs), local Area Networks (LANs), metropolitan Area Networks (MANs), and the like. The network may be wireless such that the nodes may communicate with each other via one or more wireless protocols (e.g., WLAN, wi-Fi, bluetooth, etc.). In some cases, the nodes may exchange data in the form of one or more data packets. For example, the sensor devices 104-1 through 104-n may generate data packets by packetizing data indicative of the measurements into data packets and transmitting the data packets to the monitoring system 108 via the first network 106.

The monitoring system 108 may be configured to analyze the measurements and selectively report indications of the measurements. According to various implementations, the monitoring system 108 may average the measurements over time and report the average. In other words, the monitoring system 108 may report an average of the previous a measurements taken during the time interval, where a is a positive integer. For example, the monitoring system 108 may report an arithmetic average of measurements taken over the previous hour. In some examples, the monitoring system 108 may not report every measurement value. For example, the monitoring system 108 may identify a plurality of measurements of the blood pressure of the first individual 102-1 taken over a period of time (e.g., one hour), determine an average of the blood pressure of the first individual 102-1 over the period of time, and report the average without reporting each measurement.

The monitoring system 108 may determine personalized baselines associated with the individuals 102-1 through 102-n based on measurements made by the sensor devices 104-1 through 104-n. For example, a baseline associated with the first individual 102-1 may be determined based on measurements made by the first sensor apparatus 104-1. In some cases, each baseline may be identified based on a plurality of measurements taken over a period of time (e.g., 1 hour to 6 hours, etc.). For example, the baseline associated with the first individual 102-1 may be an average or median of a plurality of measurements made by the first sensor apparatus 104-1 over the period of time. In some cases, the baseline may be defined as an average if the measurements have a symmetric distribution, and a median if the measurements have an asymmetric distribution. As used herein, the terms "symmetric distribution," "gaussian distribution," "normal distribution," and the like may refer to a set of samples having a sample skewness with an absolute value less than a predetermined threshold (e.g., 0.25). As used herein, the terms "asymmetric distribution," "oblique distribution," and the like may refer to a sample set having a sample skewness with an absolute value greater than or equal to a predetermined threshold (e.g., 0.25).

In some examples, the monitoring system 108 may confirm that the plurality of measurements over the period of time are stable. For example, the monitoring system 108 may identify that the variance of the plurality of measurements may be below a particular level (e.g., 5-10% of an average of the plurality of measurements, etc.). If the measurement is unstable (e.g., if the variance is above a certain level), the monitoring system 108 may not calculate the baseline.

In some cases, the monitoring system 108 may confirm that the individual has not moved, or has moved only a minimum amount, during the period of time. For example, an individual may be moving a "minimum amount" when the individual is determined to move less than a threshold distance (e.g., less than 6 inches), less than a threshold speed or velocity (e.g., less than 1 meter/second), less than a threshold acceleration (e.g., less than 1 meter/square second), etc. The sensor devices 104-1 through 104-n may include one or more motion sensors attached to the individuals 102-1 through 102-n. For example, the sensor devices 104-1 to 104-n may include at least one accelerometer and/or at least one pressure sensor on at least one hospital bed of the individuals 102-1 to 102-n. The movement sensor may measure movement of the individuals 102-1 through 102-n and report a measurement of the movement to the monitoring system 108 via the first network 106. Because movement may affect measurements of various biological conditions, the monitoring system 108 may not set a baseline for biological conditions measured during time frames in which individuals 102-1 through 102-n are moving a non-minimum amount. The monitoring system 108 may compare the moving measurement to a threshold (e.g., threshold distance, threshold rate, threshold velocity, threshold acceleration, etc.), and identify a baseline based only on measurements during a period of time when the moving measurement is below the threshold. In various implementations, the movement threshold associated with the biological condition may be determined by monitoring movement of at least one body and the biological condition measurement. The movement threshold may be a maximum movement measurement associated with an accurate biological condition measurement. Thus, the movement threshold may be a maximum amount of movement that does not reduce the accuracy of the biological condition measurement.

In some examples, the monitoring system 108 may confirm that the individual remains in a certain position for the period of time. The sensor devices 104-1 through 104-n may include one or more position sensors associated with the individuals 102-1 through 102-n. For example, the sensor devices 104-1 to 104-n may include at least one gyroscope, at least one pressure sensor, and/or at least one accelerometer on at least one hospital bed of the individuals 102-1 to 102-n, wherein measurements from the gyroscopes, pressure sensors, and/or accelerometers may be used to identify the pose and/or position of the individuals 102-1 to 102-n. The position sensors may measure the positions of the individuals 102-1 through 102-n in real time and report the position measurements to the monitoring system 108. The monitoring system 108 may selectively establish a baseline based on biological condition measurements made while the individuals 102-1 through 102-n are in a stable position. For example, the monitoring system 108 may use the location measurements to confirm that the first individual 102-1 has not changed location within a particular time period, and may identify a baseline biological condition based on measurements made during the particular time period. In some cases, the monitoring system 108 may selectively establish a baseline based on biological condition measurements made when the individuals 102-1 to 102-n are in a predetermined location (e.g., the individuals 102-1 to 102-n are in a location that will be in during subsequent monitoring). For example, the monitoring system 108 may use the location measurements to confirm that the first individual 102-1 is in a supine position for a particular period of time, and may identify a baseline biological condition based on the measurements of the first individual 102-1 over the particular period of time.

In some cases, the monitoring system 108 may confirm that the individuals 102-1 to 102-n have not been administered a drug (e.g., drug), biologic, drug (Pharmaceutical), etc.) that positively alters the biological condition of the individual during the period of time. For example, when salbutamol (albutero a 1) is administered to an individual, the individual's heart rate increases. In some examples, the monitoring system 108 may confirm that the individual has not been administered a drug for the period of time. If there is a delay between administration and the drug affecting the biological condition, the monitoring system 108 may confirm that no drug affecting the biological condition has occurred during that period. For example, some forms of albuterol act within 15 minutes after administration, peak effects are reached 60-90 minutes after administration, and are effective within 5 hours after administration.

In some example implementations, the monitoring system 108 may determine when the first individual 102-1 has administered a particular drug (e.g., an active ingredient, a dose, a dosage form, etc.) and when the first individual 102-1 has administered the particular drug (i.e., a dosing time). The monitoring system 108 may identify the drug and the time of administration in a variety of ways. For example, the monitoring system 108 can communicate with an Electronic Medical Record (EMR) system 110 via a second network 112. The EMR system 110 may store various health profile information for the individuals 102-1 through 102-n and selectively send data indicative of the health profile information to the monitoring system 108. In various examples, the monitoring system 108 may access the EMR system 110 to identify the medication and/or the time of administration of the first individual 102-1.

The monitoring system 108 may predict when the drug will be active for the first individual 102-1. For example, the monitoring system 108 may predict a time interval during which the drug is bioavailable to the first individual 102-1. In some cases, the monitoring system 108 may access a local database indicating time intervals between dosing and the onset and/or duration of various medications, including medications administered to the first individual 102-1. Based on the time of administration of the drug, the time interval between administration and onset of the drug, and/or the duration of the drug, the monitoring system 108 may confirm that the drug administered to the first individual 102-1 is not active during the time interval in which the measurement of the biological condition is made. Thus, the monitoring system 108 may identify a baseline of the biological condition of the first individual 102-1 based on the measurements. In some cases, the monitoring system 108 does not set a baseline for the biological condition based on measurements of the biological condition taken over a period of time during which the drug may be active and/or affecting the biological condition.

As used herein, the term "confounding factor" may refer to at least one of medical treatment, surgical treatment, administration of a drug, bioactive drug, movement of an individual, location of an individual, and the like, which may affect a measure of a biological condition of an individual. In some examples, the monitoring system 108 may confirm that confounding factors associated with the first individual 102-1 are not present for a particular period of time and may identify a baseline of the biological condition of the first individual 102-1 based on the measured value of the biological condition for the particular period of time.

In some implementations, the monitoring system 108 may selectively set a baseline for the individuals 102-1 through 102-n based on measurements taken when the individuals 102-1 through 102-n are in a state consistent with future monitoring. For example, if the first individual 102-1 is expected to be treated with an opioid during future monitoring, the monitoring system 108 may identify a baseline respiratory rate for the first individual 102-1 based on respiratory rate measurements made when the first individual 102-1 was administered the opioid. In some cases, the monitoring system 108 does not set a baseline respiratory rate for the first individual 102-1 when the first individual 102-1 is not administered opioid. Thus, the monitoring system 108 may identify a baseline based on the conditions that the individuals 102-1 through 102-n will be in during monitoring.

In various examples, the monitoring system 108 may use previous measurements of the biological condition of the individuals 102-1 through 102-n to determine the baseline. For example, the monitoring system 108 may further analyze the measurements made by the sensor devices 104-1 through 104-n based on the health profile information. For example, the monitoring system may access the EMR system 110 to identify measurements of the biological condition 108 during a hospital admission of an individual, measurements of the biological condition of an individual during a previous hospital stay, measurements of the biological condition of an individual during a previous primary care visit, and so forth.

In various implementations, the monitoring system 108 may further identify a range of biological conditions based on the baseline. In various implementations, the "primary range," "baseline range," "personalized range," etc., for an individual may be a range of biological condition measurements defined at least in part by a baseline-related threshold. The range may be defined by an upper threshold and a lower threshold. In various implementations, the monitoring system 108 may identify at least one of the upper threshold or the lower threshold based on the baseline.

In some cases, at least one threshold may be determined by subtracting or adding an offset from the baseline. The offset may be a predetermined percentage of the baseline. For example, the offset may be 20%, 10%, 5%, or other percentage of the baseline. In some cases, the offset may be a fixed value. In some examples, the offset may be 40, 30, 20, 10, 5, or other value of the baseline measurement unit. For example, if the baseline is a baseline blood pressure value in mmHg or kPa, the offset may be 30, 20, 10, 5, or other value in mmHg or kPa. In some cases, the offset may be determined from a maximum or minimum value of the biological condition and the baseline. For example, the offset may be equal to a fixed percentage of the absolute value of the difference between the minimum or maximum value and the baseline. In some cases, the fixed percentage may be 10%, 20%, 30%, 40%, 50%, 60%, 70%, or other percentages. For example, if the baseline heart rate is 40 beats per minute and the minimum heart rate is 0 beats per minute, the offset may be 25% of the difference between 40 beats per minute and 0 beats per minute, i.e., 10 beats per minute.

In some cases, the range may be determined based on a confidence interval associated with the measurement. For example, the range may be defined as 90% confidence interval, 95% confidence interval, 99% confidence interval, etc., calculated from the stable biological condition measurements.

In various examples, the monitoring system 108 may define at least one of the upper boundary or the lower boundary independent of the baseline. In some cases, a biological condition may be associated with a boundary that indicates that an individual may be unstable regardless of the individual's baseline. For example, a heart rate of 40 beats per minute may be the lowest lower boundary, while a heart rate of 200 beats per minute may be the largest upper boundary, regardless of the individual's baseline heart rate. Thus, in some cases, the monitoring system 108 may define boundaries of the range based on predetermined levels associated with unhealthy biological conditions of any individual in the overall population.

The monitoring system 108 may monitor additional measurements of the biological condition based on a baseline and/or static or dynamic range of the biological condition from the sensor device 104 associated with the individual 102. In some cases, the monitoring system 108 may trigger an alarm in response to identifying that at least one measurement of the biological condition of the individual is likely to be outside of the range. For example, the monitoring system 108 may average the measurements of the biological condition over a particular time (e.g., one hour) and may trigger an alarm in response to identifying that the average is likely to be outside of the range. In some cases, the monitoring system 108 may trigger an alarm in response to identifying that a predetermined number (e.g., 5) of measurements of a biological condition are outside of the range for a particular period of time (e.g., 1 hour).

In some examples, the monitoring system 108 may identify a measured dynamic range for monitoring a biological condition of at least one of the individuals 102-1 through 102-n. In various circumstances, there may be a predetermined trend between the medical characteristics of the individual 102 and the biological condition. For example, albuterol may increase the heart rate of an individual after administration. In some examples, an analgesic (e.g., an opioid) may reduce blood pressure in an individual following administration. In some cases, the surgery may increase the heart rate of the patient over a longer period of time. As used herein, a "medical characteristic" of an individual may refer to medical treatment administered to the individual, surgical treatment administered to the individual, drug dose administered to the individual, biological condition of the individual (e.g., vital signs), allergy of the individual (e.g., allergy to a particular drug), genetic predisposition of the individual (e.g., genotype and/or transcriptome of the individual), and the like.

In various implementations of the present disclosure, the monitoring system 108 may identify trends between one or more medical features and a biological condition. In some examples, the monitoring system 108 may receive various health profile information for various previous patients from the EMR system 110. The monitoring system 108 may train the neural network to identify trends between medical features and biological conditions using prior patient health profile information. After training the neural network, the monitoring system 108 may use the trained neural network to identify a mathematical relationship between one or more particular medical features and a particular biological condition. In some cases, the mathematical relationship may be predetermined and stored in the monitoring system 108. For example, a mathematical relationship between a biological condition and administration of a particular drug may be identified based on a predetermined pharmacokinetic model of the bioavailability of the particular drug.

The monitoring system 108 may receive an indication of one or more medical characteristics of the individual 102. In some cases where the one or more medical features include at least one other biological condition, measurements of the other biological condition may be received from the sensor device 104. In some examples, an indication of one or more medical features may be received from the EMR system 110. For example, the monitoring system 108 may access the EMR system 110 to determine that a particular medication was administered at a particular time.

Using the mathematical relationship between the one or more medical features and the biological condition, the monitoring system 108 may adjust a primary range of the biological condition (e.g., adjust an upper threshold and/or a lower threshold) based on the indication of the one or more medical features. For example, a mathematical relationship between the dose of albuterol and the time after administration may be used to increase the lower and/or upper threshold of the heart rate range of the individual 102 within 1 hour after administering albuterol to the individual.

In some cases, the monitoring system 108 may expand or contract the range, or adjust the offset of the range, based on one or more medical features. The medical features may be associated with an increased risk of a particular pathological outcome. For example, the risk of irregular breathing of individuals taking opioids may increase. In one example, an individual with Ma Fanzeng syndrome (Marfan syndrome) may increase the risk of heart damage due to hypertension. According to various implementations, the monitoring system 108 may store various rules that associate medical features with offsets, and may adjust the primary scope based on those rules. For example, the monitoring system 108 may automatically increase the lower threshold of the individual 102's respiratory frequency range in response to identifying that an opioid has been administered to the individual 102 within the last 4 hours.

In various implementations, the monitoring system 108 may further monitor the rate of change of the additional measurements. For example, the monitoring system 108 may calculate a running average of the rate of change of the additional measurements over a given period of time (e.g., one hour). The monitoring system 108 may identify a range of rates of change that are indicative of normal conditions. For example, a range of rates of change may be identified as an amount of change that is greater than ±1%, ±5%, ±10%, ±20%, ±30% or some other percentage range over a period of one minute, one hour, etc. In some cases, the range of rates of change may be defined as 90%, 95%, 99%, or other percentage of the confidence interval with a previously determined rate of change associated with the previously sent individual measurement.

If the monitoring system 108 recognizes that at least one rate of change of the measurement of the biological condition may be outside of the range, the monitoring system 108 may trigger an alarm. For example, the monitoring system 108 may trigger an alarm in response to identifying that the average rate of change is outside of the range. As used herein, an alarm may be "triggered" when the monitoring system 108 causes output of a signal associated with the alarm. For example, the monitoring system 108 may output an indication of the alarm on a monitor (or some other output device associated with the monitoring system 108), the monitoring system 108 may generate and send a signal indicative of the alarm to an external device that outputs an indication of the alarm, and so on. In some cases, the monitoring system 108 may trigger an alarm in response to identifying that the rate of change of a predetermined number (e.g., 5) of measurements of biological conditions remains outside of this range for a particular period of time (e.g., 1 hour).

In some cases, the monitoring system 108 may trigger an alarm when one of the biological condition measurements or rates of change is outside of its respective range and/or when both the biological condition measurements and rates of change are outside of its respective range. For example, the monitoring system 108 may selectively trigger an alarm when the biological condition is measured to be outside of the first range and/or the rate of change is measured to be outside of the second range. In some cases, the monitoring system 108 may trigger an alarm when one of the biological conditions is outside of the first range and the rate of change is outside of the second range. In some cases, the monitoring system 108 selectively triggers an alarm when multiple biological conditions (and/or associated rates of change) are outside of their respective ranges.

In some examples, if the monitoring system 108 identifies that one or more confounding factors are present during the time period in which the biological condition measurement is measured, the monitoring system 108 may not trigger an alarm. Thus, the monitoring system 108 may not trigger an alarm when abnormal biological condition measurements and/or rates of change may be caused by at least one confounding factor.

The monitoring system 108 may communicate with the 1 st through mth clinical devices 114-1 through 114-m, where m is a positive integer, through a third network 116. In various implementations, the monitoring system 108 may selectively report information about the individuals 102-1 through 102-n to the clinical devices 114-1 through 114-m. This information may be indicated in data sent from the monitoring system 108 to the clinical devices 114-1 to 114-m. In some cases, the monitoring system 108 may control, or otherwise cause, at least one user interface associated with the clinical devices 114-1 through 114-m.

The monitoring system 108 may trigger an alarm by sending a message (e.g., a signal) to the first through mth clinical devices 114-1 through 114-m. In some cases, the message may indicate individuals (e.g., the first individual 102-1) whose biological condition may be outside of the range. For example, the message may indicate the identity of the individual (e.g., name, patient identifier, etc.) or the location of the individual (e.g., bed identifier, room identifier, etc.). In some examples, the message may indicate a biological condition for which the measured value and/or the rate of change is outside of the applicable range.

According to some examples, the monitoring system 108 may cause at least one of the clinical devices 114-1 to 114-m to output an alert or alarm in response to determining that at least one biological condition of the individual is changing (e.g., at least one biological condition measurement and/or rate of change is outside of a primary range, below a lower threshold, above an upper threshold, etc.). As used herein, the term "alert" may refer to a signal that may be output from an electronic device that indicates that an individual may be deteriorating, but that the individual may not need immediate (e.g., bedside) assistance. As used herein, the term "alert" may refer to a signal that may be output from an electronic device that indicates that an individual may be in medical distress and that immediate assistance is required. In some cases, the monitoring system 108 may cause only the clinical devices 114-1 to 114-m to output an alarm or alert in response to determining that the plurality of biological conditions are changing. For example, the monitoring system 108 may instruct the first clinical device 114-1 to output an alert associated with the first individual 102-1 when the heart rate and blood pressure of the first individual 102-1 are determined to be outside of the primary range of the first individual 102-1, but the monitoring system 108 does not instruct the first clinical device 114-1 to output an alert when the heart rate of the first individual 102-1 is outside of the primary range and the blood pressure of the first individual 102-1 is within the primary range. In some examples, the monitoring system 108 may instruct the first clinical device 114-1 to output an alert associated with the first individual 102-1 when the heart rate and the body temperature of the first individual 102-1 are determined to be outside of a primary range (e.g., to indicate that the first individual 102-1 is sepsis), but the monitoring system 108 may not instruct the first clinical device 114-1 to output an alert when only one of the heart rate or the body temperature is outside of its respective primary range. In some cases, the monitoring system 108 may indicate other levels associated with various patient states to the clinical devices 114-1 to 114-m.

The clinical devices 114-1 to 114-m may output alerts and/or alarms in various ways. In some cases, the clinical devices 114-1 to 114-m may output the warnings and/or alarms as audible signals that may be heard by at least one caregiver. For example, the clinical devices 114-1 to 114-m may be pagers that indicate to a caregiver that another caregiver should be called or that an individual should be directly attended to by outputting an audible bell. In some implementations, the clinical devices 114-1 to 114-m may output the alerts and/or alarms as tactile signals that may be perceived by at least one caregiver. For example, the clinical devices 114-1 to 114-m may vibrate. According to various implementations, the clinical device may output the alert and/or alarm as a visual signal. In some examples, the clinical devices 114-1 to 114-m may display popup windows, flashing icons, colors, and various user interface elements depicting alarms. Alarms and warnings may be provided on various user interfaces of the clinical devices 114-1 to 114-m.

The alerts and/or alarms output by the clinical devices 114-1 to 114-m may prompt the caregiver to monitor the individuals 102-1 to 102-n associated with the alerts and/or alarms. In some cases, at least one caregiver may disable the alert and/or alarm through the user interface. For example, an alarm indicating that the first individual 102-1 needs additional attention may be disabled in response to a caregiver confirming the alarm and/or reaching the bedside of the first individual 102-1.

Fig. 2 shows an example of a visual interface 200 output by a clinical device 202. In some cases, the clinical device 202 shown in FIG. 2 may be any of the first through mth clinical devices 114-1 through 114-m described above with reference to FIG. 1.

In various implementations, the visual interface 200 may display the status of various individuals being monitored in a clinical environment (e.g., a hospital). In some examples where the clinical device 202 may be associated with (e.g., assigned to, carried by, etc.) a particular caregiver, the visual interface 200 may display the status of a plurality of (e.g., all) individuals whose care is managed by the particular caregiver. For example, a nurse may be responsible for managing the care of 3-10 patients in a medical ward environment or 1-2 persons in an ICU environment.

Visual interface 200 may display a table having a plurality of entries corresponding to the plurality of individuals being monitored, respectively. Each entry may include four fields, a patient identifier 204, vital signs 206, a rate of change 208, and a status 210. In a given entry, the patient identifier 204 may indicate a unique identifier of the individual being monitored. In some cases, the patient identifier 204 may include at least one of the name of the individual, the location of the individual in the medical facility (e.g., room identifier, bed identifier, etc.), an identifier assigned to the individual at the time of the hospital admission (e.g., a unique string assigned to the individual), etc.

In a given entry, vital sign 206 may indicate a measure of the biological condition of the individual and/or a running average (running average) of the measures. In some cases, vital signs 206 may be updated in real-time as biological conditions are measured. In the implementation shown in fig. 2, vital signs 206 represent heart rate measurements of the individual (e.g., in beats per minute). In some examples, vital signs 206 may additionally or alternatively represent a measure of at least one of blood pressure, percent blood oxygen saturation, respiration rate, body core temperature, or peripheral temperature of the individual and/or a sliding average of the measures. The rate of change 208 may represent the rate of change of the vital sign 206 over a given time interval. In some cases, the rate of change 208 may be represented as the rate of change between the current measurement (or average) of the vital sign 206 and the previous measurement (or average) of the vital sign 206 divided by the time interval between the acquisition of the current measurement (or average) and the acquisition of the previous measurement (or average) (or the time interval for averaging the measurements). In various implementations, the rate of change 208 may be a sliding average of rates of change between measured values and/or averages. For example, the rate of change 208 may correspond to an average rate of change of measurements made during the previous hour, the previous two hours, the previous three hours, and so on. In the example shown in fig. 2, the rate of change may be the rate of change of heart rate (e.g., in beats per square minute, beats per minute, etc.).

The status 210 of a given entry may indicate whether the individual needs assistance. Based on the individual's vital signs 206 and/or rate of change 208, the monitoring system may identify whether the individual needs assistance and cause the clinical device 202 to output a status 210 based on the identification. In the example shown in FIG. 2, the state 210 may have one of three levels, an alarm level, a warning level, and a normal level. In various implementations, the state 210 may have one of any number of levels representing varying degrees of patient state, assistance required, severity of medical condition experienced by the individual being monitored, and the like. When state 210 is at an alert level, the individual may need immediate or emergency assistance. When state 210 is at a warning level, the individual may be deteriorating, but may not require immediate assistance. When state 210 is at a normal level, the individual may be stable and not require immediate assistance.

In the example shown in fig. 2, the visual interface 200 may display the status of the first through nth individuals. In the entry corresponding to the first individual, the vital sign 206 may be displayed as "47" (e.g., beats per minute) and the rate of change 208 may be displayed as "-5" (e.g., beats per square minute). In some examples, the first individual may have a lower threshold 50 for the biological condition indicated by vital sign 206 and a lower threshold-4 for rate of change 208. Because both vital signs 206 and rate of change 208 are below the respective lower thresholds, the first individual may need immediate assistance. Thus, state 210 may correspond to "ALERT" ("alarm"). In some cases, the color of an entry indicating "ALERT" may be different from other entries corresponding to other states (e.g., "Warning" or "Normal").

In an entry corresponding to the second individual, vital sign 206 may be displayed as "49" (e.g., heart beats per minute) and rate of change 208 may be displayed as "1" (e.g., heart beats per square minute). In some cases, the second individual may have a lower threshold 50 for the biological condition indicated by vital sign 206 and a lower threshold-4 for rate of change 208. Since the second individual's vital sign 206 may be below its threshold, but the rate of change 208 may be above its threshold, the second individual may be deteriorating, but not requiring immediate assistance. Thus, state 210 may be displayed as "Warning".

In the entry corresponding to the nth individual, vital sign 206 may be displayed as "60" (beats per minute) and rate of change 208 may be displayed as "1" (beats per square minute). In some examples, the nth individual may have a lower threshold 50 for the biological condition indicated by vital sign 206 and a lower threshold of-4 for rate of change 208. Because the nth subject's vital sign 206 is below its threshold, but the rate of change 208 is above its threshold, the nth subject may not be worsening or require immediate assistance. Thus, state 210 may be displayed as "Normal".

In various implementations, the visual interface 200 may display an order of items based on the status 210 of individuals corresponding to the items. For example, the monitoring system and/or clinical device 202 may prioritize individuals based on status, and the visual interface 200 may display the order of items based on the priority of the respective individuals. In the example shown in fig. 2, the first individual may have the highest priority because the first individual may be the only individual having the "ALERT" status. Thus, an entry corresponding to the first individual may be displayed at the top of the list of entries in the visual interface 200. In addition, the second individual may have a higher priority than the nth individual because the second individual has a "Warning" status and the nth individual has a "Normal" status. Accordingly, an entry corresponding to the second individual may be displayed above an entry corresponding to the nth individual.

Fig. 3A and 3B illustrate vital sign measurements obtained semi-continuously over a period of time. For example, the measurement of vital signs may represent heart rate in beats per minute. Fig. 3A shows an example of relatively stable vital sign measurements obtained semi-continuously over a period of about 42 hours. Fig. 3B shows an example of relatively unstable vital sign measurements obtained semi-continuously over a period of about 42 hours.

In various implementations, a monitoring system (e.g., monitoring system 108) can receive and/or track measurements of vital signs over the period of time. For example, the monitoring system may receive measurements from a sensor device (e.g., sensor device 104) that measures vital signs of an individual (e.g., individual 102). The sampling period of the sensor device may be significantly shorter than the period of time during which the measurement is made. For example, in the example shown in fig. 3A and 3B, measurements are made within a sampling period of 0.1 hours. The term "sampling period" may refer to the period of time between measurements.

The measurement may change over time for various reasons. For example, the sensor device may be associated with a sensor noise level. Sensor noise may be due to physical limitations of the sensors within the sensor device, limitations of signal processing performed at the sensor device or monitoring system, electronic noise introduced as a signal representing the measured value passing through the sensor device, monitoring system, or communication interface between the sensor device and monitoring system, etc. In some cases, the measurement may change over time due to patient deterioration and/or medical instability. Random variations in vital sign measurements (e.g., due to noise) may have an insignificant effect on the average of the measurements. However, changes due to trends in vital sign measurements (e.g., due to medical instability) may significantly affect the average of the measurements.

The monitoring system may determine whether a baseline should be calculated from the measurements. In some cases, the monitoring system may determine the baseline after determining that the measurement is stable. For example, the monitoring system may identify the variance of the measurement. If the variance of the measurement is less than a particular threshold (e.g., a particular percentage of the average of the measurement), the monitoring system may determine that the measurement is stable and may establish a baseline based on the measurement.

In some implementations, the monitoring system may identify any measurements with variances less than 10% of its mean as stable, and may determine a baseline based on these stable measurements. In the example shown in fig. 3A, the average of the measurements is 52.5, based on the overall population variance of 2.1. Thus, the monitoring system may identify a baseline based on the measurements shown in fig. 3A. In some cases, the baseline may be the average itself (i.e., 52.5). However, in the example shown in fig. 3B, the average value of the measured values is 46.4, and the variance is 15.3. Thus, the monitoring system may not identify a baseline based on the measurements shown in fig. 3B.

In some cases, although the variance of the measurements depicted in fig. 3A is low, the monitoring system may not calculate a baseline from these measurements. For example, additional sensor data (not shown) may indicate that the individual is moving during the time period that the measurement was taken. In some cases, additional sensor data may indicate that the individual is in a position (e.g., standing position) other than a predetermined position (e.g., supine position) such that the measurement is not applicable to a position (e.g., supine position) where the individual is expected to monitor. In some examples, the monitoring system may determine (e.g., based on a medical record associated with an individual) that the individual has taken medications that affect the vital signs being measured. In some cases, if any of these features are determined to be suitable for the individual making the measurement, the monitoring system may not calculate a baseline from the measurement.

Fig. 4A and 4B illustrate individual vital sign measurements and rates of change. For example, the measurement of vital signs may be a heart rate measurement in beats per minute. The rate of change may be defined in hours. For example, if the vital sign measurement is a heart rate measurement, the rate of change may be determined as the number of beats per minute per hour (number of beats/(minutes hours)). In various implementations, the vital sign measurements and rates of change may be used by the monitoring system to determine whether to trigger an alarm indicating that the individual may need assistance. Fig. 4A shows vital sign measurements of an individual over a period of about 42 hours. Fig. 4B shows the same 42 hour running average of the rate of change of the vital sign measurements shown in fig. 4A as shown in fig. 4A.

As shown in fig. 4A, vital sign measurements may be centered around a baseline 402 and vary within a range defined by an upper threshold 404 and a lower threshold 406 over about the first 23 hours depicted. However, vital sign measurements may trend downward between 23 hours and 33 hours, and then may trend upward from 33 hours to about 42 hours. During the downward trend, vital sign measurements may drop below the lower threshold 406. During the upward trend, vital sign measurements may rise above the upper threshold 404.

As shown in fig. 4B, the rate of change per hour may generally remain between the upper threshold 410 and the lower threshold 412. However, at some point in time, the rate of change of hours may rise above the upper threshold 410 and fall below the lower threshold 412.

In various implementations, the monitoring system may determine whether to trigger an alarm based on vital sign measurements and/or the rate of change per hour. In some cases, the monitoring system will trigger an alarm whenever the vital sign measurement and/or the rate of change per hour are outside of their respective ranges. In some cases, the monitoring system triggers an alarm whenever the vital sign measurement falls below its lower threshold, the corresponding rate of change falls below its lower threshold, or whenever the vital sign measurement rises above its upper threshold, the corresponding rate of change rises above its upper threshold. According to some implementations, an alarm may be triggered if vital sign measurements are low and in a downward trend, or high and in an upward trend.

Referring to fig. 4A and 4B, in some cases, vital sign measurements may drop below the lower threshold 406 around the 24 hour mark, but the corresponding rate of change at the 24 hour mark is not below the lower threshold 412. Thus, in some cases, the monitoring system does not trigger an alarm at the 24 hour mark. However, at or around the 26 hour mark, the vital sign measurement drops below the lower threshold 405, and the corresponding rate of change drops below the lower threshold 412. Thus, in some examples, the monitoring system may trigger an alarm at a 26 hour mark.

In various examples, the monitoring system may identify confounding factors occurring at the 26 hour mark, such as that the individual may be moving, changing location, or using a drug with significant bioavailability at the 26 hour mark. Low vital sign measurements at the 26 hour mark and their downward trend may be attributed to this. Thus, in some of these examples, the monitoring system does not trigger an alarm at the 26 hour mark.

Fig. 5 and 6 illustrate example processes according to embodiments of the present disclosure. These processes are illustrated in logic flow diagrams, each of which represents a sequence of operations that may be implemented in hardware, software, or a combination thereof. In the context of software, these operations represent computer-executable instructions stored on one or more computer-readable storage media that, when executed by one or more processors, perform the recited operations. Generally, computer-executable instructions include routines, programs, objects, components, data structures, etc. that perform particular functions or implement particular abstract data types. The order in which the operations are described is not intended to be construed as a limitation, and any number of the operations described may be combined in any order and/or in parallel to implement such processes.

FIG. 5 illustrates an example process 500 for identifying personalized ranges of biological condition measurements that may be used to monitor an individual. According to various implementations, the process 500 may be performed by a monitoring system, such as the monitoring system 108 described above with reference to fig. 1. In some examples, at least some of the steps of process 500 may be performed by at least one processor in a monitoring system.

At 502, a processor may identify biological condition measurements of an individual measured over a period of time. In various cases, the biological condition may be a vital sign. For example, the biological condition may be at least one of heart rate, blood pressure, percent blood oxygen saturation, respiratory rate, body core temperature, or peripheral temperature of the individual.

In some cases, the processor may receive the measured values from a sensor device that generates the measured values. For example, the processor may be part of a system having at least one transceiver configured to receive signals indicative of the measurements from the sensor device, and the processor may identify the measurements based on the signals. In some cases, the measurement is identified substantially in real time. For example, the sensor device may transmit a signal in response to generating a corresponding measurement value.

According to various implementations, the processor may identify a plurality of measurements made of the biological condition over the period of time. For example, the processor may identify 5-100 measurements of biological conditions measured during the time period. The sampling period (e.g., the period of time between two measurements) may be significantly shorter than the length of the period of time during which the measurements are made. For example, the length of the sampling period may be 5 to 100 times the length of the period in which the measurement is made. In some cases, the time period for taking the measurement may be within 0.5 to 24 hours. For example, the period of time may be 1 to 6 hours.

At 504, the processor may determine that the individual is stable for the period of time. In various implementations, the processor may determine that the measurement is stable for the period of time. In some cases, the processor may receive (e.g., via a transceiver) a signal from a separate system, such as an EMR system (e.g., EMR system 110), indicating that the individual is stable.

In various examples, the processor may calculate the variance or standard deviation of the measurements. The variance (or standard deviation) may or may not be weighted. In some cases, the processor may compare the variance or standard deviation to a particular threshold. For example, if the variance is with respect to heart rate measurements, the threshold may be 10 times per minute. If the variance or standard deviation is below a particular threshold, the processor may determine that the individual is stable.

In some implementations, the processor may further calculate an average (e.g., an arithmetic average) of the measurements and use the average to determine whether the individual is stable. In various examples, the processor may compare the variance or standard deviation to a particular percentage of the mean. For example, the particular percentage may be 10% of the average. If the variance or standard deviation is below a certain percentage of the mean, the processor may determine that the individual is stable.

Although not suitable for the exemplary process 500 shown in fig. 5, in some implementations, the processor may identify individual instabilities based on signals and/or measurements from an external system. In response to the identification of the individual instability, the processor may monitor additional measurements of the biological condition until the measurements stabilize. In some examples, the processor may generate a new set of measurements by omitting early measurements (e.g., the first one or more measurements in the time period in which the measurements were made) and iterate 504 based on the new set of measurements.

At 506, the processor may identify a baseline based on the measurements. According to various implementations (e.g., when the measurements have a symmetrical distribution), the baseline may be an average (e.g., an arithmetic average) of the measurements. In some cases where the measurements have an asymmetric distribution, the baseline may be the median of the measurements. For example, the measurement of percent blood oxygen saturation may have an asymmetric distribution and the baseline percent blood oxygen saturation may be the median of the measurement.

At 508, the processor may identify a range of biological conditions based on the baseline. The range may be defined by a lower threshold and an upper threshold. The processor may define at least one of a lower threshold or an upper threshold based on the baseline. In some cases, the processor may identify the lower threshold or the upper threshold independently of the baseline. In various cases, the processor may be configured to define a lower threshold or an upper threshold for a particular biological condition at a particular level. For example, the processor may define the lower threshold of the heart rate measurement range as 40 beats per minute, independent of the baseline of the individual.

In some cases, the processor may calculate the threshold (e.g., a lower threshold or an upper threshold) by adding an offset value to the baseline. The offset value may be a positive or negative value. In some cases, the processor applies the same offset value to each range of the same biological condition. For example, the processor may apply an offset value of 10 times per minute to any range corresponding to heart rate. In some cases, the processor calculates the offset value from the baseline itself. For example, the processor may calculate a fixed percentage (e.g., 10%) of the baseline as the offset value. In various implementations, the processor uses two different offset values to calculate the two thresholds.

In some example implementations, the processor may calculate the potential threshold based on the baseline, but may not be used if the potential threshold is too extreme. For example, the processor may calculate a potential lower threshold based on the baseline, compare the potential lower threshold to an absolute lower threshold, and use the potential lower threshold only if the potential lower threshold is greater than the absolute lower threshold. In some examples, the processor may calculate a potential upper threshold value based on the baseline, compare the potential upper threshold value to an absolute upper threshold value, and use the potential upper threshold value only if the potential upper threshold value is below the absolute upper threshold value. The absolute threshold may represent a threshold biological condition measurement that should trigger an alarm for each individual, independent of the baseline. For example, the absolute lower threshold of the heart rate measurement may be the lowest heart rate required to adequately ventilate the human body, applicable to all persons, independent of resting heart rate.

In some implementations, the processor may compare additional measurements of the biological condition to the range to determine whether the health of the individual may deteriorate and/or whether the individual requires emergency assistance from a caregiver.

Fig. 6 illustrates an example process 600 for triggering an alarm based on a measured value of a biological condition. According to various implementations, the process 600 may be performed by a monitoring system, such as the monitoring system 108 described above with reference to fig. 1. In some examples, at least some steps of process 600 may be performed by at least one processor in a monitoring system.

At 602, a processor may identify a measurement of a biological condition of an individual measured over a period of time. In various cases, the biological condition may be a vital sign. For example, the biological condition may be at least one of heart rate, blood pressure, percent blood oxygen saturation, respiratory rate, body core temperature, or peripheral temperature of the individual.

In some cases, the processor may receive the measured values from a sensor device that generates the measured values. For example, the processor may be part of a system having at least one transceiver configured to receive signals indicative of the measurements from the sensor device, and the processor may identify the measurements based on the signals. In some cases, the measurement is identified substantially in real time. For example, the sensor device may transmit a signal in response to generating a corresponding measurement value.

According to various implementations, the processor may identify a plurality of measurements of the biological condition during the time period. For example, the processor may identify 5-100 measurements of biological conditions measured during the time period. The sampling period (e.g., the period of time between two measurements) may be significantly shorter than the length of the period of time during which the measurements are made. For example, the length of the sampling period may be 5 to 100 times the length of the period in which the measurement is made. In some cases, the time period for taking the measurement may be within 0.01 to 24 hours. For example, the period of time may be 0.1 to1 hour.

At 604, the processor may determine that one or more of the measurements are outside a first range associated with the individual. The first range may be previously defined (e.g., by the processor) based on a baseline of previous measurements of the biological condition of the individual. For example, the processor may identify the scope previously by performing the process 500 described with reference to fig. 5.

In some cases, the processor determines that at least one threshold number of the measurements are outside of the first range. The measurement outside the first range may be below the first range, above the first range, or a combination of both. In an exemplary case, the processor may determine that 2 to 10 consecutive measurements are outside the first range. In some examples, the processor determines that the time period may be longer than a threshold time period (e.g., the threshold may be about 0.1 to about 1 hour), and that all measurements made during the time period are outside of the first range. In various examples, 604 includes a processor that determines that one or more averages (e.g., arithmetic averages) of the measurements are outside of a first range.

At 606, the processor may determine that the rate of change of the measurement value may be outside of the second range. The rate of change outside the second range may be lower than the first range or higher than the first range. The processor may calculate the rate of change based on one or more measurements. In some cases, the processor may calculate an average rate of change of at least a subset of the measurements. For example, the processor may calculate a rate of change between each adjacent pair of measurements and the average rate of change. In some cases, the processor may calculate the rate of change based on a single pair of measurements. For example, the processor may calculate the rate of change based on a first pair of measurements outside of a first range, a last pair of measurements, and so on.

In some cases, the processor may calculate the second range based on confidence intervals of the rate of change previously calculated for the individual. For example, the processor may calculate a plurality of rates of change (e.g., a moving average rate of change, an average over an hour or some other time interval) based on previous measurements of the biological condition, and calculate the confidence interval based on the rates of change. The confidence level associated with the confidence interval may be 90%, 95%, 99%, etc. The processor may then define a second range based on the confidence interval. In some cases, the processor may calculate the second range based on a predetermined level. For example, the second range may be defined as a variation in the average of the measured values within a particular time interval (e.g., 1 hour) within a range of ±5%, ±10%, ±15%, or the like. In some examples, the processor may predetermine the second range based on the biological condition. For example, for heart rate measurements, the processor may always define the second range as ± 10 times/min every 0.1 hour.

At 608, the processor may determine whether any confounding factors are present. Confounding factors can affect an individual's biological condition measurement, sometimes in a predictable manner. Some examples of confounding factors include, for example, recent medical treatment, surgical treatment, administration, movement of the individual, change in the individual's location, and the like. In some cases, the processor may access an EMR system (e.g., EMR system 110) to identify whether confounding factors are present during that time period, or a previous predetermined time period prior to the time period during which the measurement has been made. For example, the biological condition may be heart rate and the processor may access the EMR system to determine whether the individual is administered albuterol during a period of time prior to the period of time during which the heart rate measurement is made.

Although not specifically illustrated in fig. 6, in some implementations the processor may adjust the first range and/or the second range in response to identifying the presence of confounding factors. In some cases, the processor may identify a relationship between the biological condition and the identification factor and adjust the first range accordingly. For example, the biological condition may be heart rate, the processor may identify that the individual has administered albuterol, and may increase the upper and lower thresholds of the first range in response to identifying that the individual has administered albuterol.

At 610, the processor may trigger an alarm. In various implementations, the processor may generate a message indicating the identity of the individual and/or the status of the individual, which may be transmitted to the electronic device through one or more transceivers. The electronic device may be associated with a caregiver that is able to provide assistance to the individual. In some cases, the message may cause the electronic device to output an alert associated with the individual so that the caregiver may be notified that the individual needs immediate assistance.

Fig. 7 illustrates an example system including at least one device 700. In some implementations, the system shown in fig. 7 may perform any of the functions described herein. The device 700 may be implemented by at least one of a server computer, dedicated hardware, software running on dedicated hardware, or virtualized functionality hosted on a suitable platform (e.g., cloud infrastructure). The device may be implemented as a single device or as multiple devices with components and data distributed among the multiple devices.

As shown, the device 700 includes a memory 702. In various implementations, the memory 702 may be volatile (e.g., random Access Memory (RAM)), non-volatile (e.g., read Only Memory (ROM), flash memory, etc.), or some combination of the two. The various elements stored in memory 702 may include methods, threads, processes, applications, objects, modules, or any other type of executable instructions. The elements stored in memory 702 may be non-transitory. The memory 702 may also store various files, databases, and the like.

The memory 702 may include various instructions 704, which may be used for any of the functions described herein. The memory 702 also includes a baseline determiner 706, a range determiner 708, and an alert trigger 710. The baseline determiner 706 can include instructions for determining a personalized baseline based on measurements of individual biological conditions (e.g., vital signs) of the individual. The range determiner 708 may include instructions for determining a personalized range of the biological condition based on the personalized baseline. Alarm trigger 710 may include instructions for monitoring measurements of biological conditions and triggering an alarm when the measurements are outside of a personalized range.

The instructions 704, baseline determiner 706, range determiner 708, and/or alarm trigger 710 may be executable by the processor 712 to perform operations. In some embodiments, processor 712 includes a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), or both a CPU and GPU, or other processing units or components known in the art.

As shown in fig. 7, the device 700 may also include one or more wired or wireless transceivers 714. For example, transceiver 714 may include a Network Interface Card (NIC), a network adapter, a Local Area Network (LAN) adapter, or a physical, virtual, or logical address to connect to various external devices and/or systems. Transceiver 714 may include any kind of wireless transceiver capable of participating in wireless communications, such as Radio Frequency (RF) communications. The transceiver 714 may also include other wireless modems, such as modems for Wi-Fi, wiMAX, bluetooth, or infrared communications.

Device 700 may also include additional data storage components such as magnetic disks, optical disks, or tape. These additional data storage components may include removable memory 716 and non-removable memory 718. Tangible computer readable media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules or other data.

Memory 702, removable storage 716 and non-removable storage 718 are all examples of computer-readable storage media. Computer-readable storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other storage technologies, CD-ROM, digital Versatile Disks (DVD), content Addressable Memory (CAM) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed by the device 700. Any such tangible computer-readable medium may be part of device 700.

The device 700 may also include an input device 720 and an output device 722. In some implementations, the input device 720 may include at least one of a keypad, cursor control, touch-sensitive display, voice input device, haptic feedback device, and the like. The output device 722 may include at least one of a display, speakers, a haptic output device, a printer, etc. Such devices are well known in the art and need not be discussed in detail herein.

The following clauses describe one or more exemplary embodiments of the present disclosure, alone or in combination.

1. A method includes receiving a first signal from a sensor, the first signal including information indicative of first measurements of vital signs of an individual measured over a first period of time, determining a baseline of the vital signs based on the first measurements, identifying a threshold value of the vital signs based on the baseline, receiving a second signal from the sensor, the second signal including information indicative of second measurements of vital signs of an individual measured over a second period of time, determining that at least one of the second measurements is outside a range defined by the threshold value, and transmitting a third signal indicative of an alarm to at least one clinical device in response to determining that at least one of the second measurements is outside the range.

2. The method of clause 1, wherein determining the baseline of the vital sign comprises identifying a variance of the first measurement, determining that the variance is less than a predetermined percentage of an arithmetic mean of the first measurement, wherein the threshold is identified in response to determining that the variance is less than the predetermined percentage.

3. The method of clause 1 or 2, wherein the sensor is a first sensor and the threshold is a first threshold, the method further comprising receiving a fourth signal from a second sensor, the fourth signal comprising information indicative of a third measurement of the movement of the individual over a first period of time, and determining that the third measurement is below the second threshold, wherein the first threshold is identified in response to determining that the third measurement is below the second threshold.

4. The method of any of claims 1-3, wherein the sensor is a first sensor and the threshold is a first threshold, the method further comprising receiving a fourth signal from the second sensor, the fourth signal including information indicative of a third measurement of the position of the individual over a first period of time, and determining that the individual has remained in a supine position for the first period of time based on the third measurement, wherein the first threshold is identified in response to determining that the individual has remained in a supine position.

5. The method of any one of clauses 1 to 4, further comprising determining that the drug administered to the individual is inactive for the first period of time, wherein the threshold value is identified in response to determining that the drug is inactive for the first period of time.

6. The method of any of clauses 1-5, wherein the threshold is a first threshold and the range is a first range, the method further comprising determining that the rate of change of the second measurement is outside a second range defined by a second threshold, wherein triggering the alarm is further responsive to determining that the rate of change of the second measurement is outside the second range.

7. The method of clause 6, wherein at least one of the second measurement values is determined to be below the first range and the rate of change is determined to be below the second range, or at least one of the second measurement values is determined to be above the first range and the rate of change is determined to be above the second range.

8. The method of any one of clauses 1 to 7, wherein the vital sign comprises at least one of a heart rate of the individual, a blood pressure of the individual, a percentage of blood oxygen saturation of the individual, a respiratory rate of the individual, a body core temperature of the individual, or a peripheral temperature of the individual.

9. A system includes at least one processor and memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations including receiving a first signal from a sensor, the first signal being indicative of a first measurement of vital signs of an individual over a first period of time, determining a baseline of vital signs from the first measurement, determining a threshold of vital signs from the baseline, receiving a second signal from the sensor, the second signal being indicative of a second measurement of vital signs of the individual over a second period of time, determining that at least one of the second measurements is outside a range defined by the threshold, and triggering an alarm in response to determining that at least one of the second measurements is outside the range.

10. The system of clause 9, wherein the sensor is a first sensor and the threshold is a first threshold, the operations further comprising receiving a third signal from a second sensor, the third signal being indicative of a third measurement of the movement of the individual over a second period of time, and determining that the third measurement is below a second threshold, wherein at least one of the second measurements is outside of a range defined by the threshold is determined in response to determining that the third measurement is below the second threshold.

11. The system of clause 9 or 10, wherein the sensor is a first sensor and the threshold is a first threshold, the operations further comprising receiving a third signal from a second sensor, the third signal being indicative of a third measurement of the position of the individual over a second period of time, and determining that the individual has remained in a supine position for the second period of time based on the third measurement, wherein at least one of the second measurements is determined in response to determining that the individual has remained in a supine position for the second period of time outside of a range defined by the threshold.

12. The system of any one of clauses 9 to 11, wherein the operations further comprise determining that the drug administered to the individual is inactive for a second period of time, wherein at least one of the second measurements is determined in response to determining that the drug is inactive for the second period of time outside of the range defined by the threshold.

13. The system of any one of clauses 9 to 12, wherein the threshold is a first threshold and the range is a first range, the operations further comprising determining that the rate of change of the second measurement is outside a second range defined by the second threshold, wherein triggering the alarm is further responsive to determining that the rate of change of the second measurement is outside the second range.

14. The system of clause 13, wherein at least one of the second measurements is determined to be below the first range and the rate of change is determined to be below the second range, or at least one of the second measurements is determined to be above the first range and the rate of change is determined to be above the second range.

15. The system of any of clauses 9 to 14, wherein the threshold is a first threshold and determining that at least one of the second measurements is outside of a range defined by the threshold comprises determining that a second measurement exceeding a second threshold number is outside of a range defined by the first threshold.

16. A system comprising a vital sign sensor configured to measure vital signs of an individual, a movement sensor configured to measure movement of an individual, an electronic device configured to output an alarm, at least one processor, and a memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising receiving a first signal from the vital sign sensor for a first measurement value indicative of vital signs measured during a first time period, receiving a second signal from the movement sensor for a second measurement value indicative of movement of an individual measured during the first time period, determining that the second measurement value is below a first threshold value, determining a baseline of vital signs by calculating an average value of the first measurement value based on the first measurement value, identifying a second threshold value of vital signs based on the baseline, the second threshold value being a predetermined percentage of the baseline, receiving a third signal from the vital sign sensor for a third measurement value, receiving a signal from the movement sensor for a third measurement value, determining that the second measurement value is below the first threshold value, determining that the second measurement value is outside of the first measurement value, determining that the first threshold value is outside of the first measurement value, determining that the first measurement value is within a second threshold value, the fifth signal is used to indicate an instruction to output an alert for identifying the individual.

17. The system of clause 16, wherein the range is a first range, the operations further comprising determining an average rate of change of the third measurement value, determining that the average rate of change is outside a second range, wherein the fifth signal is transmitted in response to determining that the average rate of change is outside the second range.

18. The system of clause 17, wherein determining that the rate of change is outside of a second range comprises determining that the average rate of change is greater than the second range, and wherein determining that at least one of the third measurements is outside of a first range comprises determining that at least one of the third measurements is greater than the second threshold.

19. The system of clause 17, wherein determining that the rate of change is outside of the second range comprises determining that the average rate of change is less than the second range, and wherein determining that at least one of the third measurements is outside of the first range comprises determining that at least one of the third measurements is less than the second threshold.

20. The system of any one of clauses 16 to 19, wherein the electronic device outputs the alert as at least one of a visual alert, an audible alert, or a tactile alert in response to receiving the fifth signal.

In some cases, one or more components may be referred to herein as "configured", "configurable", "operative/operable", "adaptable/adaptable", "capable", "consistent/compliant" and the like. Those skilled in the art will recognize that these terms (e.g., "configurable") may generally include active state components and/or inactive state components and/or standby state components unless the context requires otherwise.

As used herein, the term "based on" may be used synonymously with "based at least in part on" and "based at least in part on".

As used herein, the terms "comprising" and "including" and their equivalents are used interchangeably. The "devices, systems, or methods that include A, B and C" include A, B and C, but may also include other components (e.g., D). That is, the apparatus, system, or method is not limited to components A, B and C.

Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described.

Claims (11)

Translated fromChinese

1.一种由处理器执行的方法，包括：1. A method executed by a processor, comprising:从传感器接收第一信号，所述第一信号包括用于指示在第一时间段内测量的个体的生命体征的第一测量值的信息；receiving a first signal from a sensor, the first signal comprising information indicative of a first measurement of a vital sign of an individual measured during a first time period;识别所述第一测量值的方差；identifying a variance of the first measurement;确定所述第一测量值是稳定的，通过：Determine that the first measurement is stable by:确定所述第一测量值的方差小于方差阈值，和determining that a variance of the first measurement is less than a variance threshold, and通过确定第一时间段发生在向个体施用药物后大于预定时间量来确定对所述个体施用的药物在所述第一时间段内是非活性的；determining that a drug administered to the individual is inactive during the first time period by determining that the first time period occurs greater than a predetermined amount of time after administration of the drug to the individual;响应于确定所述第一测量值是稳定的，基于所述第一测量值确定所述生命体征的基线；In response to determining that the first measurement is stable, determining a baseline for the vital sign based on the first measurement;基于所述基线识别所述生命体征的阈值，所述生命体征的阈值比基线大于或小于偏移量；identifying a threshold value of the vital sign based on the baseline, the threshold value of the vital sign being greater or less than an offset from the baseline;通过确定第二时间段发生在向个体施用药物后的预定时间量内来确定向个体施用的药物在所述第二时间段内有效；determining that the drug administered to the individual is effective during the second time period by determining that the second time period occurs within a predetermined amount of time after administration of the drug to the individual;从所述传感器接收第二信号，所述第二信号包括用于指示在第二时间段内测量的个体的生命体征的第二测量值的信息；receiving a second signal from the sensor, the second signal comprising information indicative of a second measurement of a vital sign of the individual measured during a second time period;基于一个或多个医学特征的指示来调整生命体征的阈值，所述一个或多个医学特征包括：对个体实施的内科治疗、对个体实施的外科治疗、给个体施用的药物、给个体施用的药物剂量、个体的生物状况、个体的过敏症、或个体的遗传倾向；adjusting a threshold value for a vital sign based on an indication of one or more medical characteristics, the one or more medical characteristics comprising: a medical treatment administered to the individual, a surgical treatment administered to the individual, a medication administered to the individual, a dosage of a medication administered to the individual, a biological condition of the individual, an allergy of the individual, or a genetic predisposition of the individual;确定所述第二测量值中的至少一个在由所述生命体征的阈值限定的范围以外；以及determining that at least one of the second measurements is outside a range defined by a threshold value for the vital sign; and响应于确定所述第二测量值中的至少一个在所述范围以外，向至少一个临床设备发送指示警报的第三信号。In response to determining that at least one of the second measurements is outside of the range, a third signal indicative of an alarm is sent to at least one clinical device.2. 根据权利要求1所述的方法，其中，所述传感器是第一传感器，所述方法还包括：2. The method according to claim 1, wherein the sensor is a first sensor, the method further comprising:从第二传感器接收第四信号，所述第四信号包括用于指示在第一时间段内所述个体移动的第三测量值的信息；以及receiving a fourth signal from the second sensor, the fourth signal including information indicative of a third measurement of movement of the individual during the first time period; and所述确定所述第一测量值是稳定的的步骤还包括：确定所述第三测量值低于移动阈值。The step of determining that the first measurement is stable also includes determining that the third measurement is below a movement threshold.3. 根据权利要求1所述的方法，其中，所述方法还包括：3. The method according to claim 1, wherein the method further comprises:从第三传感器接收第五信号，所述第五信号包括用于指示在所述第一时间段内所述个体的位置的第四测量值的信息；以及receiving a fifth signal from a third sensor, the fifth signal including information indicating a fourth measurement of the location of the individual during the first time period; and所述确定所述第一测量值是稳定的的步骤还包括：基于所述第四测量值确定所述个体在所述第一时间段内保持了仰卧姿势。The step of determining that the first measurement is stable also includes: determining that the individual maintained a supine position during the first time period based on the fourth measurement.4.根据权利要求1所述的方法，其中，所述范围为第一范围，所述方法还包括：4. The method according to claim 1, wherein the range is a first range, and the method further comprises:确定所述第二测量值的变化率在由另一阈值限定的第二范围以外，determining that the rate of change of the second measurement value is outside a second range defined by another threshold,其中，触发警报还响应于确定所述第二测量值的变化率在所述第二范围以外。Wherein triggering the alarm is also responsive to determining that the rate of change of the second measurement value is outside the second range.5.根据权利要求4所述的方法，其中：5. The method according to claim 4, wherein:确定所述第二测量值中的至少一个在所述第一范围以外包括：Determining that at least one of the second measurements is outside of the first range comprises:确定所述第二测量值中的至少一个低于下阈值，并且determining that at least one of the second measurements is below a lower threshold, and确定所述第二测量值的变化率在所述第二范围以外包括：Determining that the rate of change of the second measurement value is outside the second range includes:确定所述变化率低于第二下阈值；或者determining that the rate of change is below a second lower threshold; or确定所述第二测量值中的至少一个在所述第一范围以外包括：Determining that at least one of the second measurements is outside of the first range comprises:确定所述第二测量值中的至少一个高于上阈值，并且determining that at least one of the second measurements is above an upper threshold, and确定所述第二测量值的变化率在所述第二范围以外包括：Determining that the rate of change of the second measurement value is outside the second range includes:确定所述变化率高于所述上阈值。It is determined that the rate of change is above the upper threshold.6.根据权利要求1-5任意一项所述的方法，其中：6. The method according to any one of claims 1 to 5, wherein:所述生命体征包括所述个体的心率、所述个体的血压、所述个体的血氧饱和度百分比、所述个体的呼吸频率、所述个体的体核温度或所述个体的外周温度中的至少一个。The vital sign includes at least one of the individual's heart rate, the individual's blood pressure, the individual's blood oxygen saturation percentage, the individual's respiratory rate, the individual's core temperature, or the individual's peripheral temperature.7. 一种系统，包括：7. A system comprising:至少一个处理器；以及at least one processor; and存储器，其存储指令，当由所述至少一个处理器执行时，所述指令使所述至少一个处理器执行以下操作：A memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform the following operations:如权利要求1至6中任一项所述的方法。The method according to any one of claims 1 to 6.8.一种系统，包括：8. A system comprising:生命体征传感器，其配置成测量个体的生命体征；a vital sign sensor configured to measure a vital sign of an individual;移动传感器，其配置为测量个体的移动；a motion sensor configured to measure movement of an individual;电子设备，其配置为输出警报；an electronic device configured to output an alarm;至少一个处理器；以及at least one processor; and存储器，其存储指令，当由所述至少一个处理器执行时，所述指令使所述至少一个处理器执行以下操作，包括：A memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations including:从传感器接收第一信号，所述第一信号包括用于指示在第一时间段内进行的个体的生命体征的第一测量值；receiving a first signal from a sensor, the first signal comprising a first measurement indicative of a vital sign of an individual taken over a first time period;确定所述第一测量值的方差；determining a variance of the first measurement;确定所述第一测量值是稳定的，通过：Determine that the first measurement is stable by:确定所述第一测量值的方差小于方差阈值，和determining that a variance of the first measurement is less than a variance threshold, and通过确定第一时间段发生在向个体施用药物后大于预定时间量来确定对所述个体施用的药物在所述第一时间段内是非活性的；determining that a drug administered to the individual is inactive during the first time period by determining that the first time period occurs greater than a predetermined amount of time after administration of the drug to the individual;响应于确定所述第一测量值是稳定的，基于所述第一测量值确定所述生命体征的基线；In response to determining that the first measurement is stable, determining a baseline for the vital sign based on the first measurement;基于所述基线识别所述生命体征的阈值，所述生命体征的阈值比基线大于或小于偏移量；identifying a threshold value of the vital sign based on the baseline, the threshold value of the vital sign being greater or less than an offset from the baseline;通过确定第二时间段发生在向个体施用药物后的预定时间量内来确定向个体施用的药物在所述第二时间段内有效；determining that the drug administered to the individual is effective during the second time period by determining that the second time period occurs within a predetermined amount of time after administration of the drug to the individual;从所述传感器接收第二信号，所述第二信号包括用于指示在所述第二时间段内进行的个体的生命体征的第二测量值；receiving a second signal from the sensor, the second signal comprising a second measurement indicative of a vital sign of the individual taken during the second time period;基于一个或多个医学特征的指示来调整生命体征的阈值，所述一个或多个医学特征包括：对个体实施的内科治疗、对个体实施的外科治疗、给个体施用的药物、给个体施用的药物剂量、个体的生物状况、个体的过敏症、或个体的遗传倾向；adjusting a threshold value for a vital sign based on an indication of one or more medical characteristics, the one or more medical characteristics comprising: a medical treatment administered to the individual, a surgical treatment administered to the individual, a medication administered to the individual, a dosage of a medication administered to the individual, a biological condition of the individual, an allergy of the individual, or a genetic predisposition of the individual;确定所述第二测量值中的至少一个在由所述生命体征的阈值限定的范围以外；以及determining that at least one of the second measurements is outside a range defined by a threshold value for the vital sign; and响应于确定所述第二测量值中的至少一个在所述范围以外，触发警报。In response to determining that at least one of the second measurements is outside of the range, an alarm is triggered.9. 根据权利要求8所述的系统，其中，所述传感器是第一传感器，所述操作还包括：9. The system of claim 8, wherein the sensor is a first sensor, the operations further comprising:从第二传感器接收第四信号，所述第四信号包括用于指示在第一时间段内进行的所述个体移动的第三测量值；以及receiving a fourth signal from the second sensor, the fourth signal comprising a third measurement indicative of movement of the individual during the first time period; and确定所述第一测量值是稳定的还包括：确定所述第三测量值低于移动阈值。Determining that the first measurement is stable also includes determining that the third measurement is below a movement threshold.10. 根据权利要求8所述的系统，其中，所述传感器是第一传感器，所述操作还包括：10. The system of claim 8, wherein the sensor is a first sensor, the operations further comprising:从第三传感器接收第五信号，所述第五信号包括用于指示在所述第一时间段内进行的所述个体的位置的第四测量值；以及receiving a fifth signal from a third sensor, the fifth signal comprising a fourth measurement indicative of a location of the individual taken during the first time period; and确定所述第一测量值是稳定的还包括：基于所述第四测量值确定所述个体在所述第一时间段内保持了仰卧姿势。Determining that the first measurement is stable also includes determining that the individual maintained a supine position during the first time period based on the fourth measurement.11. 根据权利要求8所述的系统，其中，所述范围为第一范围，所述操作还包括：11. The system according to claim 8, wherein the range is a first range, and the operation further comprises:确定所述第二测量值的变化率在由另一阈值限定的第二范围以外，其中，确定所述第二测量值的变化率在所述第二范围以外后，还执行触发警报的操作；或者Determining that the rate of change of the second measurement value is outside a second range defined by another threshold, wherein after determining that the rate of change of the second measurement value is outside the second range, further performing an operation of triggering an alarm; or其中：in:确定所述第二测量值中的至少一个在所述第一范围以外包括：Determining that at least one of the second measurements is outside of the first range comprises:确定所述第二测量值中的至少一个低于下阈值，并且determining that at least one of the second measurements is below a lower threshold, and确定所述第二测量值的变化率在所述第二范围以外包括：Determining that the rate of change of the second measurement value is outside the second range includes:确定所述变化率低于第二下阈值；或者determining that the rate of change is below a second lower threshold; or确定所述第二测量值中的至少一个在所述第一范围以外包括：Determining that at least one of the second measurements is outside of the first range comprises:确定所述第二测量值中的至少一个高于上阈值，并且determining that at least one of the second measurements is above an upper threshold, and确定所述第二测量值的变化率在所述第二范围以外包括：Determining that the rate of change of the second measurement value is outside the second range includes:确定所述变化率高于所述上阈值。It is determined that the rate of change is above the upper threshold.